CUSTOMER SUPPORT

Weekly digest of undocumented answers, auto-drafted into Confluence

Each week, scans resolved support tickets for answers with no matching KB article, clusters the recurring ones, and creates draft Confluence pages for the top gaps.

CategoryCustomer Support
Enginesim
Difficultyintermediate
Triggerschedule
Steps6
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerWeekly schedule
  • ActionPull resolved tickets with no linked articleZendeskZendesk
  • ActionCluster and rank undocumented answersOpenAI
  • LogicKeep only high-frequency gap clusters
  • ActionDraft an article per clusterOpenAI
  • OutputCreate draft Confluence pagesConfluenceConfluence

What it does

Runs on a weekly schedule, looks back over every resolved ticket, and finds the answers agents wrote without referencing an existing knowledge base article. It groups similar undocumented answers so a question asked ten times becomes one draft, then creates Confluence draft pages for the highest-frequency gaps — turning a week of repeated typing into a short, prioritized documentation backlog.

When to use it

Use it when you want a steady documentation cadence rather than per-ticket noise. Ideal for teams whose canonical docs live in Confluence and who want to fix the most common gaps first.

How it works

  1. 1A weekly schedule fires the run.
  2. 2The flow queries resolved tickets from the past seven days in Zendesk and isolates replies with no linked article.
  3. 3OpenAI clusters the from-scratch answers by topic and ranks them by how often each gap recurred.
  4. 4A logic step keeps only clusters above a frequency threshold.
  5. 5For each surviving cluster, OpenAI writes a full article draft.
  6. 6Each draft is created as an unpublished Confluence page in the docs space for an owner to review.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect ZendeskTickets, queues, knowledge base.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect ConfluenceSpaces, pages, blueprints.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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